OPERATION MANAGEMENT
2nd Edition
ISBN: 9781260242423
Author: CACHON
Publisher: MCG
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Chapter 15, Problem 13CQ
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To explain: If the given statement is true or false.
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Chapter 15 Solutions
OPERATION MANAGEMENT
Ch. 15 - When creating a time seriesbased forecast for the...Ch. 15 - Prob. 2CQCh. 15 - Prob. 3CQCh. 15 - Prob. 4CQCh. 15 - Prob. 5CQCh. 15 - Prob. 6CQCh. 15 - Prob. 7CQCh. 15 - Prob. 8CQCh. 15 - Using the moving average forecast, is it possible...Ch. 15 - Prob. 10CQ
Ch. 15 - Prob. 11CQCh. 15 - Prob. 12CQCh. 15 - Prob. 13CQCh. 15 - Deseasonalizing old demand data is the process of...Ch. 15 - Prob. 15CQCh. 15 - Prob. 1PACh. 15 - Prob. 2PACh. 15 - Prob. 3PACh. 15 - A police station had to deploy police officers for...Ch. 15 - MyApp is a small but growing startup that sees...Ch. 15 - Prob. 6PACh. 15 - Prob. 7PACh. 15 - Prob. 1CCh. 15 - CASE INTERNATIONAL ARRIVALS The U.S. Department of...Ch. 15 - Prob. 3C
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- The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?arrow_forwardAt the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.arrow_forwardThe Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?arrow_forward
- Dilberts Department Store is trying to determine how many Hanson T-shirts to order. Currently the shirts are sold for 21, but at later dates the shirts will be offered at a 10% discount, then a 20% discount, then a 40% discount, then a 50% discount, and finally a 60% discount. Demand at the full price of 21 is believed to be normally distributed with mean 1800 and standard deviation 360. Demand at various discounts is assumed to be a multiple of full-price demand. These multiples, for discounts of 10%, 20%, 40%, 50%, and 60% are, respectively, 0.4, 0.7, 1.1, 2, and 50. For example, if full-price demand is 2500, then at a 10% discount customers would be willing to buy 1000 T-shirts. The unit cost of purchasing T-shirts depends on the number of T-shirts ordered, as shown in the file P10_36.xlsx. Use simulation to determine how many T-shirts the company should order. Model the problem so that the company first orders some quantity of T-shirts, then discounts deeper and deeper, as necessary, to sell all of the shirts.arrow_forwardThe file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?arrow_forwardManagement of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.arrow_forward
- Forecast error is calculated as: Actual - Forecast O Forecast - Actual (Forecast - Actual) ^ 2 Absolute (Actual - Forecast) (Actual - Forecast) ^ 2arrow_forwardA newly operated company producing household items would want to forecast its sales volume for the next month. It has been in operation for ten (10) months now. For the past ten (10) months, forecast and sales data for its top selling Item A are as follow: Time Period Forecasted Value Actual Sales (Quantity) 10th month 405 345 9th month 400 380 8th month 410 400 7th month 370 375 6th month 330 360 5th month 320 325 4th month 320 315 3rd month 305 300 2nd month 290 295 1st month 300 280 The operations manager observes the fluctuations on the sales quantity over the 10-month period that the company is in operation. To forecast for the 11th month, the team decided to evaluate options on what forecasting method to use. Their options are: To use the Moving Average Method using the sales data for the past 10 months, To use the Exponential Smoothing Average assigning a smoothing constant of .6 and To use the Trend-adjusted Exponential Smoothing assigning smoothing constants α =…arrow_forwardThe manager of Carpet City outlet needs to make an accurate forecast of demand for Soft Shag Carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpet from one of Carpet City’s many competitors. The manager has collected the following demand data for the past 8 months: Month Demand for Soft Shag Carpet (1000 yd) 1 8 2 12 3 7 4 9 5 15 6 11 7 10 8 12 Required showing all workings: Compute a 3-month moving average forecast for months 4 through 9. Compute a weighted 3-month moving average forecast for months 4 through 9. Assign weights of 0.55, 0.33 and 0.12 to the months in sequence, starting with the most recent month.arrow_forward
- Moving Average method is always superior to Weighted moving average method for time series forecast a.True b.Falsearrow_forwardForecast error is measured using the following formula. O a. Actual value = Forecast value O b. Forecast value = Actual value O C. Actual value - Forecast value o d. Forecast value - Actual valuearrow_forwardWhat advantages does adjusted exponential smoothing have over a linear trend line for forecasted demand that exhibits a trend?arrow_forward
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